A Unified Air-Sea Interface for Fully Coupled Atmosphere-Wave-Ocean Models for Improving Intensity Prediction of Tropical Cyclones

2011 ◽  
Author(s):  
Shuyi S. Chen ◽  
Mark A. Donelan ◽  
Ashwanth Srinivasan ◽  
Rick Allard ◽  
Tim Campbell ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Intensity Prediction ◽  
Ocean Models ◽  
Fully Coupled

Sea-state dependency of air-sea fluxes for high winds in ECMWF Earth System Model

2020 ◽  
Author(s):  
Jean Bidlot
Keyword(s):  
Drag Coefficient ◽  
Tropical Cyclones ◽  
Coupled System ◽  
Wave Model ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Sea State ◽  
Medium Range ◽  
Fully Coupled

<p>The global analyses and medium range forecasts from the European Centre for Medium range Weather Forecasts rely on a state-of-the-art Numerical Weather Prediction (NWP) system. To best represent the air-sea exchanges, it is tightly coupled to an ocean wave model.  As part of ECMWF approach to Earth System Model, it is also coupled to a global ocean model for all its forecasting systems from the medium range up to the seasonal time scale.</p><p>Because the feedback from and to the ocean can be significant, it is only in the fully coupled system that parameterisation for air-sea processes should be revisited. For instance, it is now accepted that the drag coefficient should generally attained maximum values for storm winds but should level or even decrease for very strong winds, namely in tropical cyclones or intense mid-latitude wind storms.</p><p>A modification of the wind input source was tested, whereby the Charnock coefficient estimated by the wave model and therefore the drag coefficient sharply reduce for large winds (> 30 m/s). As a consequence, ECMWF tendency to under predict strong tropical cyclones was sharply alleviated, in better agreement with observational evidence. This change is now planned for operational implementation with the next model cycle (CY47R1, June 2020).</p><p>Experimental evidences also point to a sea state/wind dependency of the heat and moisture fluxes.  Following an extension of the wind wave generation theory, a sea state dependent parameterisation for the roughness length scales for heat and humidity has been tested. Again, a proper assessment of the different parameterisations warrants the fully coupled system. Experimentations so far indicate the benefit of such change. Ongoing work aims at future operational implementation.</p>

scholarly journals Ending Storm Version of the 7-day Weighted Analog Intensity Prediction Technique for Western North Pacific Tropical Cyclones

2017 ◽  
Vol 32 (6) ◽  
pp. 2229-2235 ◽  
Author(s):  
Hsiao-Chung Tsai ◽  
Russell L. Elsberry
Keyword(s):  
Tropical Cyclones ◽  
North Pacific ◽  
Western North Pacific ◽  
Storm Events ◽  
Training Set ◽  
Intensity Prediction ◽  
Prediction Technique ◽  
The Mean ◽  
Forecast Interval ◽  
Intensity Spread

Abstract The weighted analog intensity prediction technique for western North Pacific (WAIP) tropical cyclones (TCs) was the first guidance product for 7-day intensity forecasts, which is skillful in the sense that the 7-day errors are about the same as the 5-day errors. Independent tests of this WAIP version revealed an increasingly large intensity overforecast bias as the forecast interval was extended from 5 to 7 days, which was associated with “ending storms” due to landfall, extratropical transition, or to delayed development. Thus, the 7-day WAIP has been modified to separately forecast ending and nonending storms within the 7-day forecast interval. The additional ending storm constraint in the selection of the 10 best historical analogs is that the intensity at the last matching point with the target TC track cannot exceed 50 kt (where 1 kt = 0.51 m s−1). A separate intensity bias correction calculated for the ending storm training set reduces the mean biases to near-zero values and thereby improves the mean absolute errors in the 5–7-day forecast interval for the independent set. A separate calibration of the intensity spreads for the training set to ensure that 68% of the verifying intensities will be within the 12-h WAIP intensity spread values results in smaller spreads (or higher confidence) for ending storms in the 5–7-day forecast intervals. Thus, some extra effort by the forecasters to identify ending storm events within 7 days will allow improved intensity and intensity spread forecast guidance.

scholarly journals A Last Glacial Maximum forcing dataset for ocean modelling

2020 ◽  
Vol 12 (4) ◽  
pp. 2971-2985
Author(s):  
Anne L. Morée ◽  
Jörg Schwinger
Keyword(s):  
Last Glacial Maximum ◽  
Coupled Model ◽  
Research Data ◽  
Glacial Maximum ◽  
Specific Humidity ◽  
Wave Radiation ◽  
Last Glacial ◽  
Model Set ◽  
Ocean Models ◽  
Fully Coupled

Abstract. Model simulations of the Last Glacial Maximum (LGM; ∼ 21 000 years before present) can aid the interpretation of proxy records, can help to gain an improved mechanistic understanding of the LGM climate system, and are valuable for the evaluation of model performance in a different climate state. Ocean-ice only model configurations forced by prescribed atmospheric data (referred to as “forced ocean models”) drastically reduce the computational cost of palaeoclimate modelling compared to fully coupled model frameworks. While feedbacks between the atmosphere and ocean and sea-ice compartments of the Earth system are not present in such model configurations, many scientific questions can be addressed with models of this type. Our dataset supports simulations of the LGM in a forced ocean model set-up while still taking advantage of the complexity of fully coupled model set-ups. The data presented here are derived from fully coupled palaeoclimate simulations of the Palaeoclimate Modelling Intercomparison Project phase 3 (PMIP3). The data are publicly accessible at the National Infrastructure for Research Data (NIRD) Research Data Archive at https://doi.org/10.11582/2020.00052 (Morée and Schwinger, 2020). They consist of 2-D anomaly forcing fields suitable for use in ocean models that employ a bulk forcing approach and are optimized for use with CORE forcing fields. The data include specific humidity, downwelling long-wave and short-wave radiation, precipitation, wind (v and u components), temperature, and sea surface salinity (SSS). All fields are provided as climatological mean anomalies between LGM and pre-industrial (PI) simulations. These anomaly data can therefore be added to any pre-industrial ocean forcing dataset in order to obtain forcing fields representative of LGM conditions as simulated by PMIP3 models. Furthermore, the dataset can be easily updated to reflect results from upcoming and future palaeo-model intercomparison activities.

scholarly journals Reduced tropical cyclone densities and ocean effects due to anthropogenic greenhouse warming

2020 ◽  
Vol 6 (51) ◽  
pp. eabd5109
Author(s):  
Jung-Eun Chu ◽  
Sun-Seon Lee ◽  
Axel Timmermann ◽  
Christian Wengel ◽  
Malte F. Stuecker ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Cold Water ◽  
Relevant Information ◽  
Forced Response ◽  
System Model ◽  
Greenhouse Warming ◽  
Earth System ◽  
Tropical Oceans ◽  
Ocean Models ◽  
Hadley Cells

Tropical cyclones (TCs) are extreme storms that form over warm tropical oceans. Along their tracks, TCs mix up cold water, which can further affect their intensity. Because of the adoption of lower-resolution ocean models, previous modeling studies on the TC response to greenhouse warming underestimated such oceanic feedbacks. To address the robustness of TC projections in the presence of mesoscale air-sea interactions and complex coastal topography, we conduct greenhouse warming experiments using an ultrahigh-resolution Earth System Model. We find that a projected weakening of the rising branches of the summer Hadley cells suppresses future TC genesis and TC-generated ocean cooling. The forced response is similar to recent observational trends, indicating a possible emergence of the anthropogenic signal beyond natural variability levels. In the greenhouse warming simulations, landfalling TCs intensify, both in terms of wind speed and associated rainfall. Our modeling results provide relevant information for climate change adaptation efforts.

scholarly journals A Last Glacial Maximum forcing dataset for ocean modelling

2019 ◽  
Author(s):  
Anne L. Morée ◽  
Jörg Schwinger
Keyword(s):  
Last Glacial Maximum ◽  
Computational Cost ◽  
Coupled Model ◽  
Glacial Maximum ◽  
Sea Surface Salinity ◽  
Specific Humidity ◽  
Data Set ◽  
Last Glacial ◽  
Ocean Models ◽  
Fully Coupled

Abstract. Model simulations of the Last Glacial Maximum (LGM, ~ 21 000 years before present) can aid the interpretation of proxy records, help to gain an improved mechanistic understanding of the LGM climate system and are valuable for the evaluation of model performance in a different climate state. Ocean-ice only model configurations forced by prescribed atmospheric data (referred to as “forced ocean models”) drastically reduce the computational cost of paleoclimate modelling as compared to fully coupled model frameworks. While feedbacks between the atmosphere and ocean-sea-ice compartments of the Earth system are not present in such model configurations, many scientific questions can be addressed with models of this type. The data presented here are derived from fully coupled paleoclimate simulations of the Palaeoclimate Modelling Intercomparison Project (PMIP3). The data are publicly accessible at the NIRD Research Data Archive at https://doi.org/10.11582/2019.00011 (Morée and Schwinger, 2019). They consist of 2-D anomaly forcing fields suitable for use in ocean models that employ a bulk forcing approach. The data include specific humidity, downwelling longwave and shortwave radiation, precipitation, wind (v and u components), temperature and sea surface salinity (SSS). All fields are provided as climatological mean anomalies between LGM and pre-industrial times. These anomaly data can therefore be added to any pre-industrial ocean forcing data set in order to obtain forcing fields representative of LGM conditions as simulated by PMIP3 models. These forcing data provide a means to simulate the LGM in a computationally efficient way, while still taking advantage of the complexity of fully coupled model set-ups. Furthermore, the dataset can be easily updated to reflect results from upcoming and future paleo model intercomparison activities.

scholarly journals The Climatological Effect of Saharan Dust on Global Tropical Cyclones in a Fully Coupled GCM

2018 ◽  
Vol 123 (10) ◽  
pp. 5538-5559 ◽  
Author(s):  
Jeffrey D. O. Strong ◽  
Gabriel A. Vecchi ◽  
Paul Ginoux
Keyword(s):  
Tropical Cyclones ◽  
Saharan Dust ◽  
Coupled Gcm ◽  
Fully Coupled

scholarly journals Toward Improving High-Resolution Numerical Hurricane Forecasting: Influence of Model Horizontal Grid Resolution, Initialization, and Physics

2012 ◽  
Vol 27 (3) ◽  
pp. 647-666 ◽  
Author(s):  
Sundararaman G. Gopalakrishnan ◽  
Stanley Goldenberg ◽  
Thiago Quirino ◽  
Xuejin Zhang ◽  
Frank Marks ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Initial Conditions ◽  
Horizontal Resolution ◽  
Grid Resolution ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Decay Component ◽  
Intensity Prediction ◽  
Hurricane Forecasting ◽  
Parent Domain ◽  
The Impact

Abstract This paper provides an account of the performance of an experimental version of the Hurricane Weather Research and Forecasting system (HWRFX) for 87 cases of Atlantic tropical cyclones during the 2005, 2007, and 2009 hurricane seasons. The HWRFX system was used to study the influence of model grid resolution, initial conditions, and physics. For each case, the model was run to produce 126 h of forecast with two versions of horizontal resolution, namely, (i) a parent domain at a resolution of about 27 km with a 9-km moving nest (27:9) and (ii) a parent domain at a resolution of 9 km with a 3-km moving nest (9:3). The former was selected to be consistent with the current operational resolution, while the latter is the first step in testing the impact of finer resolutions for future versions of the operational model. The two configurations were run with initial conditions for tropical cyclones obtained from the operational Geophysical Fluid Dynamics Laboratory (GFDL) and HWRF models. Sensitivity experiments were also conducted with the physical parameterization scheme. The study shows that the 9:3 HWRFX system using the GFDL initial conditions and a system of physics similar to the operational version (HWRF) provides the best results in terms of both track and intensity prediction. Use of the HWRF initial conditions in the HWRFX model provides reasonable skill, particularly when used in cases with initially strong storms (hurricane strength). However, initially weak storms (below hurricane strength) posed special challenges for the models. For the weaker storm cases, none of the predictions from the HWRFX runs or the operational GFDL forecasts provided any consistent improvement when compared to the operational Statistical Hurricane Intensity Prediction Scheme with an inland decay component (DSHIPS).

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